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Dongare DB, Nishad SS, Mastoli SY, Saraf SA, Srivastava N, Dey A. High-throughput sequencing: a breakthrough in molecular diagnosis for precision medicine. Funct Integr Genomics 2025; 25:22. [PMID: 39838192 DOI: 10.1007/s10142-025-01529-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2024] [Revised: 01/03/2025] [Accepted: 01/07/2025] [Indexed: 01/23/2025]
Abstract
High-resolution insights into the nucleotide arrangement within an organism's genome are pivotal for deciphering its genetic composition, function, and evolutionary trajectory. Over the years, nucleic acid sequencing has been instrumental in driving significant advancements in genomics and molecular biology. The advent of high-throughput or next-generation sequencing (NGS) technologies has revolutionized whole genome sequencing, revealing novel and intriguing features of genomes, such as single nucleotide polymorphisms and lethal mutations in both coding and non-coding regions. These platforms provide a practical approach to comprehensively identifying and analyzing whole genomes with remarkable throughput, accuracy, and scalability within a short time frame. The resulting data holds immense potential for enhancing healthcare systems, developing novel and personalized therapies, and preparing for future pandemics and outbreaks. Given the wide array of available high-throughput sequencing platforms, selecting the appropriate technology based on specific needs is crucial. However, there is limited information regarding sample preparation, sequencing principles, and output data to facilitate a comparative evaluation of these platforms. This review details various NGS technologies and approaches, examining their advantages, limitations, and future potential. Despite being in their early stages and facing challenges, ongoing advancements in NGS are expected to yield significant future benefits.
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Affiliation(s)
- Dipali Barku Dongare
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER)-Raebareli, Lucknow, 226002, India
| | - Shaik Shireen Nishad
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER)-Raebareli, Lucknow, 226002, India
| | - Sakshi Y Mastoli
- Department of Pharmaceutics, National Institute of Pharmaceutical Education and Research (NIPER)-Raebareli, Lucknow, 226002, India
| | - Shubhini A Saraf
- Department of Pharmaceutics, National Institute of Pharmaceutical Education and Research (NIPER)-Raebareli, Lucknow, 226002, India
| | - Nidhi Srivastava
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER)-Raebareli, Lucknow, 226002, India
| | - Abhishek Dey
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER)-Raebareli, Lucknow, 226002, India.
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Lightbody G, Haberland V, Browne F, Taggart L, Zheng H, Parkes E, Blayney JK. Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application. Brief Bioinform 2019; 20:1795-1811. [PMID: 30084865 PMCID: PMC6917217 DOI: 10.1093/bib/bby051] [Citation(s) in RCA: 97] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 05/01/2018] [Indexed: 12/28/2022] Open
Abstract
There has been an exponential growth in the performance and output of sequencing technologies (omics data) with full genome sequencing now producing gigabases of reads on a daily basis. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), computational considerations, data governance and clinical translation are the greatest rate-limiting steps. To ensure that the analysis, management and interpretation of such extensive omics data is exploited to its full potential, key factors, including sample sourcing, technology selection and computational expertise and resources, need to be considered, leading to an integrated set of high-performance tools and systems. This article provides an up-to-date overview of the evolution of HTS and the accompanying tools, infrastructure and data management approaches that are emerging in this space, which, if used within in a multidisciplinary context, may ultimately facilitate the development of personalized medicine.
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Affiliation(s)
- Gaye Lightbody
- School of Computing, Ulster University, Newtownabbey, UK
| | - Valeriia Haberland
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Fiona Browne
- School of Computing, Ulster University, Newtownabbey, UK
| | | | - Huiru Zheng
- School of Computing, Ulster University, Newtownabbey, UK
| | - Eileen Parkes
- Centre for Cancer Research & Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Queen's University, Belfast, UK
| | - Jaine K Blayney
- Centre for Cancer Research & Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Queen's University, Belfast, UK
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Richmond PA, Wasserman WW. Introduction to Genomic Analysis Workshop: A catalyst for engaging life-science researchers in high throughput analysis. F1000Res 2019; 8:1221. [PMID: 31602299 PMCID: PMC6774052 DOI: 10.12688/f1000research.19320.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/19/2019] [Indexed: 11/20/2022] Open
Abstract
Researchers in the life sciences are increasingly faced with the task of obtaining compute resources and training to analyze large, high-throughput technology generated datasets. As demand for compute resources has grown, high performance computing (HPC) systems have been implemented by research organizations and international consortiums to support academic researchers. However, life science researchers lack effective time-of-need training resources for utilization of these systems. Current training options have drawbacks that inhibit the effective training of researchers without experience in computational analysis. We identified the need for flexible, centrally-organized, easily accessible, interactive, and compute resource specific training for academic HPC use. In our delivery of a modular workshop series, we provided foundational training to a group of researchers in a coordinated manner, allowing them to further pursue additional training and analysis on compute resources available to them. Efficacy measures indicate that the material was effectively delivered to a broad audience in a short time period, including both virtual and on-site students. The practical approach to catalyze academic HPC use is amenable to diverse systems worldwide.
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Affiliation(s)
- Phillip A. Richmond
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, Vancouver, British Columbia, V5Z 4H4, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, V6T 1Z4, Canada
| | - Wyeth W. Wasserman
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, Vancouver, British Columbia, V5Z 4H4, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, V6T 1Z4, Canada
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Larcombe L, Hendricusdottir R, Attwood TK, Bacall F, Beard N, Bellis LJ, Dunn WB, Hancock JM, Nenadic A, Orengo C, Overduin B, Sansone SA, Thurston M, Viant MR, Winder CL, Goble CA, Ponting CP, Rustici G. ELIXIR-UK role in bioinformatics training at the national level and across ELIXIR. F1000Res 2017; 6. [PMID: 28781748 PMCID: PMC5521157 DOI: 10.12688/f1000research.11837.1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/19/2017] [Indexed: 11/20/2022] Open
Abstract
ELIXIR-UK is the UK node of ELIXIR, the European infrastructure for life science data. Since its foundation in 2014, ELIXIR-UK has played a leading role in training both within the UK and in the ELIXIR Training Platform, which coordinates and delivers training across all ELIXIR members. ELIXIR-UK contributes to the Training Platform’s coordination and supports the development of training to address key skill gaps amongst UK scientists. As part of this work it acts as a conduit for nationally-important bioinformatics training resources to promote their activities to the ELIXIR community. ELIXIR-UK also leads ELIXIR’s flagship Training Portal, TeSS, which collects information about a diverse range of training and makes it easily accessible to the community. ELIXIR-UK also works with others to provide key digital skills training, partnering with the Software Sustainability Institute to provide Software Carpentry training to the ELIXIR community and to establish the Data Carpentry initiative, and taking a lead role amongst national stakeholders to deliver the StaTS project – a coordinated effort to drive engagement with training in statistics.
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Affiliation(s)
- L Larcombe
- MRC Human Genetics Unit, The Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - R Hendricusdottir
- MRC Human Genetics Unit, The Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - T K Attwood
- School of Computer Science, University of Manchester, Manchester, M13 9PL, UK
| | - F Bacall
- School of Computer Science, University of Manchester, Manchester, M13 9PL, UK
| | - N Beard
- School of Computer Science, University of Manchester, Manchester, M13 9PL, UK
| | - L J Bellis
- Department of Genetics, University of Cambridge, Cambridge, CB2 3EH, UK
| | - W B Dunn
- Birmingham Metabolomics Training Centre, School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
| | | | - A Nenadic
- The Software Sustainability Institute, University of Manchester, Manchester, M13 9PL, UK
| | - C Orengo
- University College London, London, WC1E 6BT, UK
| | - B Overduin
- Edinburgh Genomics, University of Edinburgh, Edinburgh, EH9 3FL, UK
| | - S-A Sansone
- Oxford e-Research Centre, University of Oxford, Oxford, OX1 3QG, UK
| | - M Thurston
- Oxford e-Research Centre, University of Oxford, Oxford, OX1 3QG, UK
| | - M R Viant
- Birmingham Metabolomics Training Centre, School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - C L Winder
- Birmingham Metabolomics Training Centre, School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - C A Goble
- School of Computer Science, University of Manchester, Manchester, M13 9PL, UK
| | - C P Ponting
- MRC Human Genetics Unit, The Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - G Rustici
- Department of Genetics, University of Cambridge, Cambridge, CB2 3EH, UK
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